Understanding tree architecture, form and function in the tropics

了解热带地区的树木结构、形态和功能

• 批准号: NE/P011780/1
• 负责人: Mathias Disney
• 金额: $ 25.94万
• 依托单位: University College London
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2017
• 资助国家: 英国
• 起止时间: 2017 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=NE%2FP011780%2F1
• 关键词: Understanding; tree; architecture; form; function

The basic shape and branching structure of a tree can be distinctive and characteristic, yet there exists no consistent dataset quantifying how tree form varies across species and how it is related to other functional traits of a tree. Understanding the variation in structure and form of trees is important in order to link tree physiology to tree performance, scale fluxes of water and carbon within and among trees, and understand constraints on tree growth and mortality. These topics hold great importance in the field of ecosystem science, especially in light of current and future changes to climate. It is surprising, therefore, that tree structure and form are currently neglected areas of study. There are two primary reasons for this neglect: 1) it is difficult and time-consuming to quantify tree structure in-situ and 2) there is a lack of theory that explicitly links tree form parameters with physiological function.Recent developments in technology and theory now enable us to overcome these limitations. In this proposal we aim to use new ground-based 3D terrestrial laser scanning technologies (TLS) in combination with recently developed theoretical frameworks to measure and compare tree architecture. We focus on the tropics, since (i) they host the vast majority of broadleaf tree diversity and play a disproportionate role in global and regional carbon and water fluxes, and (ii) the high species diversity of tropical forests (typically 100-250 tree species per hectare) means we can sample a large number of species under almost identical climate and soil conditions, making it more likely to detect overall tendencies in tree form response to environment that are not dominated by the peculiarity of a particular species. Specifically, we will employ TLS to collect highly-detailed 3D structural information from mature rainforest trees spanning contrasting environments ranging from cloud forests to wet rainforests to dry savanna, and contrasting biogeographical histories from the cloud forests of the Andes through legume-dominated forests of Amazonia and Africa, through the dipterocarp-dominated tall forests of Borneo, to the ancient rainforest flora of Australia. All field sites are locations where we have already collected information of the leaf and wood traits of a number of tropical trees. We plan to achieve three goals: i) definition of quantitative classes of tree form using advanced imaging and computational techniques, ii) development of an understanding of the degree of covariance between tree form and tree leaf and wood functional traits, and the degree of phylogenetic constraint and plasticity in tree form, iii) testing and refinement of metabolic-scaling based approaches to scaling fluxes and productivity of tropical tree communities. Over the course of three years our team will:1) Create a database of branch- and canopy-level trait data collected from our field campaigns. 2) Use variation in branching architecture and canopy structure traits to define a suite of branching and canopy traits that allow for the classification of tree form.3) Assess the scaling of tree form traits within trees and integrate the scaling of tree-form into a mechanistic plant scaling framework.4) Explore the link between tree-form traits and leaf and wood traits to determine a whole-tree integrated economics spectrum. In doing so, we hope to acquire a mechanistic understanding of the relationship between tree form, function, phylogeny and environment over a large spatial scale. We expect to find that behind the dazzling variety of shapes and forms found in trees hides a remarkably similar architecture based on fundamental, shared principles.

树木的基本形状和分支结构可能是独特的和有特征的，但没有一致的数据集量化树木形态在不同物种之间的变化以及它如何与树木的其他功能特征相关。了解树木的结构和形式的变化是很重要的，以链接树的生理树的性能，水和碳的尺度通量内和之间的树木，并了解树木生长和死亡的限制。这些主题在生态系统科学领域非常重要，特别是考虑到当前和未来的气候变化。因此，令人惊讶的是，树木的结构和形式是目前被忽视的研究领域。这种忽视主要有两个原因：1）原位量化树木结构是困难和耗时的; 2）缺乏将树木形态参数与生理功能明确联系起来的理论。在这项提案中，我们的目标是使用新的地面三维地面激光扫描技术（TLS）结合最近开发的理论框架来测量和比较树的结构。我们把重点放在热带，因为（i）它们拥有绝大多数阔叶树的多样性，在全球和区域碳和水通量中发挥着不成比例的作用，（ii）热带森林的物种多样性高（通常每公顷100-250个树种）意味着我们可以在几乎相同的气候和土壤条件下对大量物种进行采样，使其更有可能检测到树形对不受特定物种特性支配的环境的响应的总体趋势。具体来说，我们将采用TLS收集高度详细的三维结构信息，从成熟的热带雨林树木跨越不同的环境，从云雾森林到潮湿的热带雨林到干燥的热带稀树草原，并对比从安第斯山脉的云雾森林到亚马逊河和非洲的豆科植物为主的森林，通过婆罗洲的龙脑香为主的高大森林，到澳大利亚的古老雨林植物群的地理历史。所有的现场位置，我们已经收集了一些热带树木的叶和木材性状的信息。我们计划实现三个目标：i）使用先进的成像和计算技术定义树形的数量类别，ii）理解树形与树叶和木材功能性状之间的协方差程度，以及树形中系统发育约束和可塑性的程度，㈢测试和改进以代谢定标为基础的方法，以定标热带树木群落的通量和生产力。在三年的时间里，我们的团队将：1）创建一个从我们的田间活动中收集的分支和冠层水平性状数据的数据库。2)使用分支架构和冠层结构性状的变化来定义一套分支和冠层性状，允许树的形式分类。3）评估树内的树的形式性状的缩放和集成树的形式的缩放到一个机械植物缩放框架。4）探索树的形式性状和叶和木材性状之间的联系，以确定一个整树综合经济谱。在这样做的过程中，我们希望在大的空间尺度上获得对树木形态、功能、繁殖和环境之间关系的机械理解。我们希望在树木令人眼花缭乱的各种形状和形式背后，隐藏着一个基于基本的，共享的原则的非常相似的架构。

项目成果

Developing new biomass allometric equations based on terrestrial laser scanning

基于地面激光扫描开发新的生物量异速生长方程

• 发表时间: 2018
• 作者: Calders K

New insights into large tropical tree mass and structure from direct harvest and terrestrial lidar.

• DOI: 10.1098/rsos.201458
• 发表时间: 2021-02-10
• 期刊: Royal Society open science
• 影响因子: 3.5
• 作者: Burt A;Boni Vicari M;da Costa ACL;Coughlin I;Meir P;Rowland L;Disney M
• 通讯作者: Disney M

Variability and bias in active and passive ground-based measurements of effective plant, wood and leaf area index

• DOI: 10.1016/j.agrformet.2018.01.029
• 发表时间: 2018-04-15
• 期刊: AGRICULTURAL AND FOREST METEOROLOGY
• 影响因子: 6.2
• 作者: Calders, Kim;Origo, Niall;Lewis, Philip
• 通讯作者: Lewis, Philip

Assessment of Bias in Pan-Tropical Biomass Predictions

• DOI: 10.3389/ffgc.2020.00012
• 发表时间: 2020-02-20
• 期刊: FRONTIERS IN FORESTS AND GLOBAL CHANGE
• 影响因子: 3.2
• 作者: Burt, Andrew;Calders, Kim;Disney, Mathias
• 通讯作者: Disney, Mathias

Realistic Forest Stand Reconstruction from Terrestrial LiDAR for Radiative Transfer Modelling

• DOI: 10.3390/rs10060933
• 发表时间: 2018-06-01
• 期刊: REMOTE SENSING
• 影响因子: 5
• 作者: Calders, Kim;Origo, Niall;Lewis, Philip
• 通讯作者: Lewis, Philip